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60  'sequence-types': u'\nEmulating container types\n*************************\n\nThe following methods can be defined to implement container objects.\nContainers usually are sequences (such as lists or tuples) or mappings\n(like dictionaries), but can represent other containers as well.  The\nfirst set of methods is used either to emulate a sequence or to\nemulate a mapping; the difference is that for a sequence, the\nallowable keys should be the integers *k* for which "0 <= k < N" where\n*N* is the length of the sequence, or slice objects, which define a\nrange of items. (For backwards compatibility, the method\n"__getslice__()" (see below) can also be defined to handle simple, but\nnot extended slices.) It is also recommended that mappings provide the\nmethods "keys()", "values()", "items()", "has_key()", "get()",\n"clear()", "setdefault()", "iterkeys()", "itervalues()",\n"iteritems()", "pop()", "popitem()", "copy()", and "update()" behaving\nsimilar to those for Python\'s standard dictionary objects.  The\n"UserDict" module provides a "DictMixin" class to help create those\nmethods from a base set of "__getitem__()", "__setitem__()",\n"__delitem__()", and "keys()". Mutable sequences should provide\nmethods "append()", "count()", "index()", "extend()", "insert()",\n"pop()", "remove()", "reverse()" and "sort()", like Python standard\nlist objects.  Finally, sequence types should implement addition\n(meaning concatenation) and multiplication (meaning repetition) by\ndefining the methods "__add__()", "__radd__()", "__iadd__()",\n"__mul__()", "__rmul__()" and "__imul__()" described below; they\nshould not define "__coerce__()" or other numerical operators.  It is\nrecommended that both mappings and sequences implement the\n"__contains__()" method to allow efficient use of the "in" operator;\nfor mappings, "in" should be equivalent of "has_key()"; for sequences,\nit should search through the values.  It is further recommended that\nboth mappings and sequences implement the "__iter__()" method to allow\nefficient iteration through the container; for mappings, "__iter__()"\nshould be the same as "iterkeys()"; for sequences, it should iterate\nthrough the values.\n\nobject.__len__(self)\n\n   Called to implement the built-in function "len()".  Should return\n   the length of the object, an integer ">=" 0.  Also, an object that\n   doesn\'t define a "__nonzero__()" method and whose "__len__()"\n   method returns zero is considered to be false in a Boolean context.\n\nobject.__getitem__(self, key)\n\n   Called to implement evaluation of "self[key]". For sequence types,\n   the accepted keys should be integers and slice objects.  Note that\n   the special interpretation of negative indexes (if the class wishes\n   to emulate a sequence type) is up to the "__getitem__()" method. If\n   *key* is of an inappropriate type, "TypeError" may be raised; if of\n   a value outside the set of indexes for the sequence (after any\n   special interpretation of negative values), "IndexError" should be\n   raised. For mapping types, if *key* is missing (not in the\n   container), "KeyError" should be raised.\n\n   Note: "for" loops expect that an "IndexError" will be raised for\n     illegal indexes to allow proper detection of the end of the\n     sequence.\n\nobject.__missing__(self, key)\n\n   Called by "dict"."__getitem__()" to implement "self[key]" for dict\n   subclasses when key is not in the dictionary.\n\nobject.__setitem__(self, key, value)\n\n   Called to implement assignment to "self[key]".  Same note as for\n   "__getitem__()".  This should only be implemented for mappings if\n   the objects support changes to the values for keys, or if new keys\n   can be added, or for sequences if elements can be replaced.  The\n   same exceptions should be raised for improper *key* values as for\n   the "__getitem__()" method.\n\nobject.__delitem__(self, key)\n\n   Called to implement deletion of "self[key]".  Same note as for\n   "__getitem__()".  This should only be implemented for mappings if\n   the objects support removal of keys, or for sequences if elements\n   can be removed from the sequence.  The same exceptions should be\n   raised for improper *key* values as for the "__getitem__()" method.\n\nobject.__iter__(self)\n\n   This method is called when an iterator is required for a container.\n   This method should return a new iterator object that can iterate\n   over all the objects in the container.  For mappings, it should\n   iterate over the keys of the container, and should also be made\n   available as the method "iterkeys()".\n\n   Iterator objects also need to implement this method; they are\n   required to return themselves.  For more information on iterator\n   objects, see Iterator Types.\n\nobject.__reversed__(self)\n\n   Called (if present) by the "reversed()" built-in to implement\n   reverse iteration.  It should return a new iterator object that\n   iterates over all the objects in the container in reverse order.\n\n   If the "__reversed__()" method is not provided, the "reversed()"\n   built-in will fall back to using the sequence protocol ("__len__()"\n   and "__getitem__()").  Objects that support the sequence protocol\n   should only provide "__reversed__()" if they can provide an\n   implementation that is more efficient than the one provided by\n   "reversed()".\n\n   New in version 2.6.\n\nThe membership test operators ("in" and "not in") are normally\nimplemented as an iteration through a sequence.  However, container\nobjects can supply the following special method with a more efficient\nimplementation, which also does not require the object be a sequence.\n\nobject.__contains__(self, item)\n\n   Called to implement membership test operators.  Should return true\n   if *item* is in *self*, false otherwise.  For mapping objects, this\n   should consider the keys of the mapping rather than the values or\n   the key-item pairs.\n\n   For objects that don\'t define "__contains__()", the membership test\n   first tries iteration via "__iter__()", then the old sequence\n   iteration protocol via "__getitem__()", see this section in the\n   language reference.\n',

64 setdefault
72 setdefault(key[, default])\n\n If *key* is in the dictionary, return its value. If not, insert\n *key* with a value of *default* and return *default*. *default*\n defaults to "None".\n\n update([other])\n\n Update the dictionary with the key/value pairs from *other*,\n overwriting existing keys. Return "None".\n\n "update()" accepts either another dictionary object or an\n iterable of key/value pairs (as tuples or other iterables of\n length two). If keyword arguments are specified, the dictionary\n is then updated with those key/value pairs: "d.update(red=1,\n blue=2)".\n\n Changed in version 2.4: Allowed the argument to be an iterable\n of key/value pairs and allowed keyword arguments.\n\n values()\n\n Return a copy of the dictionary\'s list of values. See the note\n for "dict.items()".\n\n viewitems()\n\n Return a new view of the dictionary\'s items ("(key, value)"\n pairs). See below for documentation of view objects.\n\n New in version 2.7.\n\n viewkeys()\n\n Return a new view of the dictionary\'s keys. See below for\n documentation of view objects.\n\n New in version 2.7.\n\n viewvalues()\n\n Return a new view of the dictionary\'s values. See below for\n documentation of view objects.\n\n New in version 2.7.\n\n\nDictionary view objects\n=======================\n\nThe objects returned by "dict.viewkeys()", "dict.viewvalues()" and\n"dict.viewitems()" are *view objects*. They provide a dynamic view on\nthe dictionary\'s entries, which means that when the dictionary\nchanges, the view reflects these changes.\n\nDictionary views can be iterated over to yield their respective data,\nand support membership tests:\n\nlen(dictview)\n\n Return the number of entries in the dictionary.\n\niter(dictview)\n\n Return an iterator over the keys, values or items (represented as\n tuples of "(key, value)") in the dictionary.\n\n Keys and values are iterated over in an arbitrary order which is\n non-random, varies across Python implementations, and depends on\n the dictionary\'s history of insertions and deletions. If keys,\n values and items views are iterated over with no intervening\n modifications to the dictionary, the order of items will directly\n correspond. This allows the creation of "(value, key)" pairs using\n "zip()": "pairs = zip(d.values(), d.keys())". Another way to\n create the same list is "pairs = [(v, k) for (k, v) in d.items()]".\n\n Iterating views while adding or deleting entries in the dictionary\n may raise a "RuntimeError" or fail to iterate over all entries.\n\nx in dictview\n\n Return "True" if *x* is in the underlying dictionary\'s keys, values\n or items (in the latter case, *x* should be a "(key, value)"\n tuple).\n\nKeys views are set-like since their entries are unique and hashable.\nIf all values are hashable, so that (key, value) pairs are unique and\nhashable, then the items view is also set-like. (Values views are not\ntreated as set-like since the entries are generally not unique.) Then\nthese set operations are available ("other" refers either to another\nview or a set):\n\ndictview & other\n\n Return the intersection of the dictview and the other object as a\n new set.\n\ndictview | other\n\n Return the union of the dictview and the other object as a new set.\n\ndictview - other\n\n Return the difference between the dictview and the other object\n (all elements in *dictview* that aren\'t in *other*) as a new set.\n\ndictview ^ other\n\n Return the symmetric difference (all elements either in *dictview*\n or *other*, but not in both) of the dictview and the other object\n as a new set.\n\nAn example of dictionary view usage:\n\n >>> dishes = {\'eggs\': 2, \'sausage\': 1, \'bacon\': 1, \'spam\': 500}\n >>> keys = dishes.viewkeys()\n >>> values = dishes.viewvalues()\n\n >>> # iteration\n >>> n = 0\n >>> for val in values:\n ... n += val\n >>> print(n)\n 504\n\n >>> # keys and values are iterated over in the same order\n >>> list(keys)\n [\'eggs\', \'bacon\', \'sausage\', \'spam\']\n >>> list(values)\n [2, 1, 1, 500]\n\n >>> # view objects are dynamic and reflect dict changes\n >>> del dishes[\'eggs\']\n >>> del dishes[\'sausage\']\n >>> list(keys)\n [\'spam\', \'bacon\']\n\n >>> # set operations\n >>> keys & {\'eggs\', \'bacon\', \'salad\'}\n {\'bacon\'}\n',